Construction enterprise digital project management platform

Abstract

The invention relates to the technical field of construction project management, discloses a construction enterprise digital project management platform, and aims to solve the problems of data islands, low information transmission efficiency, insufficient decision support and the like in a traditional project management mode. The platform is composed of a user interface layer, a business logic layer, an infrastructure layer and a data access layer, has a comprehensive project management function, and comprises a project management unit, a material purchasing unit, a construction management unit, a quality control unit and the like. The core function of the system is that the fusion analysis module can perform standardization processing on data of each business unit, realize centralized storage and management of the data, form a unified data view, perform deep data mining and analysis by using a machine learning algorithm, construct a prediction model, a classification model and a clustering model, and perform data classification and clustering. And comprehensive data support is provided for enterprise decision making. The platform effectively improves the project management efficiency and quality of construction enterprises, and promotes the digital transformation of the construction enterprises.

Description

Technical Field

[0001] The present invention relates to the technical field of construction project management, and in particular to a digital project management platform for construction enterprises. Background Art

[0002] With the rapid development of information technology, construction companies have an increasing demand for digital and intelligent project management. Traditional project management methods often rely on manual operations and paper documents, and have problems such as data silos, inefficient information transmission, and insufficient decision support, making it difficult to meet the modern construction companies' requirements for efficient, accurate, and transparent management.

[0003] The existing project management system has obvious defects in data integration. Data between business units are often stored in different formats, making it difficult to form a unified data view, resulting in serious data silos and the inability to achieve cross-departmental data sharing and collaboration. This not only increases the complexity of data management, but also limits the depth and breadth of data analysis, making it difficult to provide comprehensive data support for corporate decision-making.

[0004] Traditional project management has limited means for data analysis. Most systems can only provide basic data query and reporting functions, lacking in-depth data mining and analysis capabilities. With the expansion of enterprise scale and the increase in business complexity, the demand for data analysis is becoming increasingly urgent, such as predictive analysis, trend analysis, correlation analysis, etc. These functions are often difficult to achieve or inefficient in existing systems. Therefore, we propose a digital project management platform for construction enterprises. Summary of the invention

[0005] The purpose of the present invention is to provide a digital project management platform for construction enterprises to solve the problems raised in the above background technology.

[0006] To achieve the above-mentioned object, the present invention provides the following technical solutions: a digital project management platform for a construction enterprise, comprising a user interface layer, a business logic layer, an infrastructure layer and a data access layer;

[0007] The user interface layer includes a user interaction module and a rights management module; the user interaction module is used to provide a visual user interface and process the interaction logic between the user and the platform; the rights management module is used to manage and control user access rights;

[0008] The business logic layer includes a basic management module and a fusion analysis module;

[0009] The basic management module includes a project management unit, a material procurement management unit, a construction management unit, a quality control unit, a bidding management unit, a safety risk management unit, a subcontract management unit and a business management unit;

[0010] The fusion analysis module includes a data integration unit and an analysis model construction unit; the data integration unit is used to standardize the data of each business logic layer module, including data format and naming specifications, and through data integration technology, centrally store and manage the relevant data scattered in each business logic layer module to form a unified data view; the analysis model construction unit is used to build data analysis models according to business needs, including prediction models, classification models and clustering models, and use machine learning algorithms to conduct in-depth mining and analysis of the integrated data;

[0011] The infrastructure layer includes a database module, a service management module and a gateway module; the database module provides data storage functions, including a data cache unit, a persistent storage unit and a column storage unit, the data cache unit is used to temporarily store frequently accessed data, the persistent storage unit is used to store important data for a long time, and the column storage unit is used to store and analyze a large amount of structured data; the service management module uses a microservice architecture to uniformly manage the modules of the business logic layer; the gateway module provides connection services to the user interface layer, establishes a channel for data transmission, and matches the target microservice instance accessed by the user interface layer through the routing address;

[0012] The data access layer includes a data interface module and a database connection module; the data interface module is used to provide the HTTP interface and Websocket message push for page requests to the user interface layer; the database connection module establishes a connection channel between the business logic layer and the database module, allowing both to perform safe and stable data reading and writing operations.

[0013] Preferably, the project management unit is used to handle the overall business process related to the project, including project planning, progress tracking, cost control and resource allocation;

[0014] The material procurement management unit is used to process business processes related to material procurement, including procurement plan formulation, supplier selection, purchase order generation and procurement execution;

[0015] The construction management unit is used to process business processes related to the construction site, including construction progress control, construction quality management and construction safety management;

[0016] The quality control unit is used to process business processes related to engineering quality, including quality plan formulation, quality control standard setting and quality inspection execution;

[0017] The bidding management unit is used to assist enterprises in managing the entire bidding process of engineering projects, including bidding information management, bidding preparation and compilation, bidding review and decision-making;

[0018] The safety risk management unit is used to assess and manage safety risks in the project, including recording of safety hazards, assessment of risk levels and formulation of risk response measures;

[0019] The subcontract management unit is responsible for handling business processes related to subcontracting, including the selection of subcontractors, the signing of subcontract contracts and the execution of subcontract work;

[0020] The business management unit is responsible for processing business-related business processes, including contract signing, modification, execution and settlement.

[0021] Preferably, the service management module provides unified registration, status monitoring and message bus communication functions for microservice instances. The message bus adopts the communication mechanism of the event bus, so that the microservices in the service layer can communicate loosely through events.

[0022] Automatically manage and schedule microservice instances, including service deployment, start, stop, and restart;

[0023] Perform data monitoring and log management on microservices, and collect service operation data and log information.

[0024] Preferably, the database module adopts an active-active architecture, including an active node and a standby node, the two nodes back up each other when processing data, and when the active node fails, requires maintenance or upgrade, the standby node takes over the service.

[0025] Preferably, the data analysis model includes a prediction model, a classification model and a clustering model, the prediction model includes a project completion time prediction model, a cost prediction model and a market demand prediction model; the classification model includes a project risk level classification model, a supplier credit evaluation classification model and an engineering quality classification model; the clustering model includes a project type clustering model and a customer demand clustering model.

[0026] Preferably, the data interface module provides an HTTP interface for page requests, for receiving page requests sent by the user interface layer;

[0027] Provides a Websocket message push interface to implement real-time message push from the server to the user interface layer;

[0028] Parse and process received page requests and message push requests, and call corresponding microservices to perform business logic processing based on the type and content of the request;

[0029] Return the processed results of the microservice to the user interface layer.

[0030] Preferably, the gateway module maintains a routing table to record the address information of each microservice instance; matches the routing address in the request of the user interface layer in the routing table, finds the corresponding target microservice instance, and forwards the request to the instance.

[0031] Preferably, the data integration unit defines and identifies each business logic layer module as a data source, and formulates a data extraction strategy based on business requirements and data characteristics, wherein the extraction strategy includes a full extraction measurement and an incremental extraction strategy.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The present invention standardizes the data of each business logic layer module through a data integration unit, and centrally stores and manages it, effectively eliminating the data island phenomenon, realizing cross-departmental data sharing and collaboration, and improving the efficiency and consistency of data management.

[0034] The infrastructure layer uses a microservice architecture to uniformly manage the modules of the business logic layer, improving the scalability and maintainability of the system. The database module provides a variety of data storage methods to meet the data storage requirements of different business scenarios. The present invention covers all aspects of project management through the basic management module, including project management, material procurement, construction management and quality control, etc., realizing the comprehensive digitization and intelligence of project management, and improving the efficiency and quality of project management.

[0035] The fusion analysis module uses machine learning algorithms to conduct in-depth mining and analysis of the integrated data, and constructs a variety of data analysis models including prediction models, classification models, and clustering models, providing enterprises with comprehensive and in-depth data analysis support, helping to improve the accuracy and timeliness of decision-making.

[0036] The present invention provides a complete digital project management solution for construction companies, which helps them achieve digital transformation and improve their overall competitiveness and market adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is the overall structure diagram of the present invention;

[0038] Figure 2 This is a schematic diagram of data transmission at the business logic layer. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] See also Figure 1-2 ,The present invention provides a technical solution: a digital project management platform for a construction enterprise, a user interface layer, a business logic layer, an infrastructure layer and a data access layer.

[0041] The user interface layer is the window for users to interact with the platform, which mainly includes the user interaction module and the permission management module. The user interaction module is responsible for providing a visual user interface and processing the interaction logic between the user and the platform to ensure that users can operate conveniently and quickly. The permission management module is responsible for managing and controlling user access rights to ensure the security and confidentiality of platform data.

[0042] The business logic layer is mainly responsible for handling the management of various business logics. This layer includes the basic management module and the fusion analysis module. The basic management module covers all aspects of project management, including project management unit, material procurement management unit, construction management unit, quality control unit, bidding management unit, safety risk management unit, subcontract management unit and business management unit, among which:

[0043] The project management unit is used to handle the overall business processes related to projects, including project planning, progress tracking, cost control and resource allocation.

[0044] The material procurement management unit is used to handle business processes related to material procurement, including procurement plan formulation, supplier selection, purchase order generation and procurement execution.

[0045] The construction management unit is used to handle business processes related to the construction site, including construction progress control, construction quality management and construction safety management.

[0046] The quality control unit is used to handle business processes related to engineering quality, including quality plan formulation, quality control standard setting, and quality inspection execution.

[0047] The bidding management unit is used to assist enterprises in managing the entire bidding process of engineering projects, including bidding information management, bid preparation and compilation, bid review and decision-making.

[0048] The safety risk management unit is used to assess and manage safety risks in the project, including the recording of safety hazards, the assessment of risk levels and the formulation of risk response measures.

[0049] The subcontract management unit is responsible for handling business processes related to subcontracting, including the selection of subcontractors, the signing of subcontract contracts and the execution of subcontract work.

[0050] The business management unit is responsible for handling business-related business processes, including contract signing, modification, execution and settlement.

[0051] The above units together constitute a complete project management process.

[0052] The fusion analysis module is responsible for integrating and analyzing the data of each business logic layer module. The data integration unit standardizes the data of each module, including data format and naming specifications, and centrally stores and manages the scattered data through data integration technology to form a unified data view. The analysis model construction unit builds data analysis models such as prediction models, classification models, and clustering models according to business needs, and uses machine learning algorithms to conduct in-depth mining and analysis of the integrated data to provide data support for corporate decision-making.

[0053] The infrastructure layer provides underlying support for the platform, including database modules, service management modules, and gateway modules. The database module provides data storage functions, including data cache units, persistent storage units, and column storage units. The data cache unit is used to temporarily store frequently accessed data to improve data access speed; the persistent storage unit is used to store important data for a long time to ensure data reliability and security; the column storage unit is used to store and analyze large amounts of structured data to improve data analysis efficiency.

[0054] The service management module uses a microservice architecture to manage the modules of the business logic layer in a unified manner, ensuring the scalability and maintainability of the platform. The gateway module provides connection services to the user interface layer, establishes a data transmission channel, and matches the target microservice instance accessed by the user interface layer through the routing address to achieve fast data transmission and access.

[0055] The data access layer is a bridge for data interaction between the platform and the database, including the data interface module and the database connection module. The data interface module is responsible for providing the HTTP interface and Websocket message push for page requests to the user interface layer to realize data interaction between users and the platform. The database connection module establishes a connection channel between the business logic layer and the database module to ensure safe and stable data reading and writing operations between the two.

[0056] The invention will be further described below in conjunction with Examples 1 to 3:

[0057] Embodiment 1:

[0058] The service management module provides a unified registration function for microservice instances. Under the microservice architecture, each service instance needs to be registered in the service management module so that it can be discovered and called by other services. The registration information includes key information such as service name, version number, deployment address, etc., which will be stored in the registration center of the service management module. Spring Cloud Eureka or Zookeeper can be used as the service registration center. When the microservice instance is started, it will automatically register its own information with the registration center. Other microservices can query the address information of the required service through the registration center, thereby realizing the call between services. The service management module is also responsible for real-time monitoring of the status of the microservice instance. By sending heartbeat detection signals regularly, the service management module can obtain the running status of the service instance in real time, including whether it is online, response time, and load status.

[0059] The message bus in the service management module uses the communication mechanism of the event bus. The event bus allows the microservices in the service layer to communicate through events without directly calling each other's service interfaces. This communication method reduces the dependencies between microservices and improves the scalability and flexibility of the system. Event bus technology can use message middleware such as SpringCloud Bus or RabbitMQ as the event bus. Microservice instances publish and subscribe to events through the event bus to achieve a loosely coupled communication method.

[0060] The service management module also provides automated management and scheduling functions for microservice instances, including full lifecycle management such as service deployment, start, stop, and restart. Through the service management module, developers can easily manage microservice instances without having to perform tedious operations manually. Specifically, the service management module provides a visual management interface through which developers can deploy and configure services. At the same time, the service management module also supports automated scripts and API interfaces, allowing developers to implement automated management and scheduling of services programmatically. Using container technologies such as Docker, microservice instances are packaged into container images for deployment. Containerized deployment improves the portability and deployment efficiency of services. Using container orchestration tools such as Kubernetes, microservice instances are automatically managed and scheduled. Kubernetes provides functions such as service deployment, start, stop, restart, and capacity expansion and contraction.

[0061] The database module adopts a dual-active architecture to improve data reliability and service continuity. The architecture includes an active node and a standby node. The two nodes back up each other when processing data, ensuring that when any node fails, requires maintenance or upgrades, the other node can take over the service. The implementation of the dual-active architecture is as follows:

[0062] ①Node configuration:

[0063] Active node: responsible for processing major database read and write requests and providing real-time data services.

[0064] Standby node: Keeps real-time data synchronized with the active node and is ready to take over services at any time.

[0065] ②Data replication:

[0066] Use synchronous or asynchronous data replication mechanism to ensure data consistency between active nodes and standby nodes.

[0067] During the replication process, all data changes to the active node are synchronized to the standby node in real time.

[0068] ③Fault detection and transfer:

[0069] Implement a fault detection mechanism to regularly check the health status of active nodes.

[0070] The failover process is automatically triggered when an active node fails, requires maintenance, or is undergoing an upgrade.

[0071] The standby node takes over the service and becomes the new active node, continuing to provide data services.

[0072] ④Automatic recovery:

[0073] When the original active node returns to normal, it can be switched back to active status automatically or manually.

[0074] During this process, data changes on the standby node are synchronized back to the original active node to ensure data consistency.

[0075] The data cache unit is mainly used to store temporary data to speed up data access and reduce the access pressure on persistent storage. Redis can be used as a cache database.

[0076] The persistent storage unit is responsible for storing data that the system needs to keep for a long time, ensuring the security and reliability of the data. MySQL or PostgreSQL can be used as a persistent database.

[0077] Column storage units are mainly used to optimize query performance under large amounts of data. Especially when performing complex analysis and statistics, ClickHouse can be used as a column storage database.

[0078] Embodiment 2:

[0079] To implement the functions of the data interface module, the present invention adopts widely used Web development frameworks, such as SpringBoot, and message push technologies, such as Spring WebSocket. These technical frameworks provide rich components and tools to support the development of HTTP interfaces and Websocket interfaces, as well as request processing and response.

[0080] ①Implementation of HTTP interface:

[0081] Interface definition: Based on business requirements, define the HTTP interface for page requests, including the interface address, request method (such as GET, POST), request parameters, and response format.

[0082] Controller writing: Use the @RestController annotation in the Spring Boot framework to write an interface controller class. In the controller class, use annotations such as @RequestMapping or @GetMapping, @PostMapping, etc. to map HTTP requests to corresponding processing methods.

[0083] Request processing: In the processing method, the received HTTP request is parsed and processed. According to the type and content of the request, the corresponding microservice is called to perform business logic processing.

[0084] Response return: Encapsulate the result processed by the microservice into a response object and return it to the user interface layer through the HTTP interface.

[0085] ②Implementation of Websocket message push interface

[0086] Configure Websocket: Use the Spring WebSocket framework to configure the Websocket message push interface, including defining the Websocket endpoint, message broker, and message handler.

[0087] Establishing a connection: When the user interface layer initiates a Websocket connection request, the data interface module establishes a connection with the client and maintains the connection status.

[0088] Message push: When real-time messages need to be pushed to the user interface layer, the data interface module pushes the messages to the client through a Websocket connection.

[0089] Message processing: After receiving the push message, the client performs corresponding processing, such as updating page content, pop-up notification, etc.

[0090] ③Request parsing and processing

[0091] Request parsing: The data interface module parses the received page requests and message push requests, and extracts the parameters and data in the requests.

[0092] Calling microservices: Based on the type and content of the request, the data interface module calls the corresponding microservices to process the business logic. Complex business operations can be completed through collaboration between microservices.

[0093] Processing result return: The result processed by the microservice is returned to the data interface module, and the data interface module encapsulates the result into a response object and returns it to the user interface layer.

[0094] Spring Boot and Spring WebSocket frameworks provide efficient request processing and response mechanisms, which can quickly respond to client requests and push real-time messages.

[0095] Embodiment 3:

[0096] The data integration unit uses data integration and ETL (Extract, Transform, Load) tools, such as Apache NiFi. The Apache NiFi framework provides powerful data extraction, transformation and loading capabilities, supports data extraction from various data sources, and performs cleaning, transformation and storage.

[0097] The data integration unit first defines each business logic layer module as a data source, including database, file system, API interface, etc. Through configuration or coding, the data integration unit identifies and connects to the defined data source to obtain data and metadata information in the data source.

[0098] Data extraction strategy development includes:

[0099] Full extraction strategy: For business scenarios that require comprehensive analysis or historical data backtracking, the data integration unit formulates a full extraction strategy to extract all data from the data source.

[0100] Incremental extraction strategy: For business scenarios that require real-time updates or large amounts of data, the data integration unit formulates an incremental extraction strategy to extract only new or changed data from the data source.

[0101] According to the formulated data extraction strategy, the data integration unit configures the extraction tasks, including data source connection information, extraction conditions and extraction frequency.

[0102] The data integration unit executes the configured extraction tasks, extracts data from the data source, and performs necessary data cleaning and conversion operations.

[0103] Store the extracted and processed data in a specified target storage system, such as a data warehouse or data lake.

[0104] The prediction model includes a project completion time prediction model, a cost prediction model and a market demand prediction model; the classification model includes a project risk level classification model, a supplier credit evaluation classification model and an engineering quality classification model; the clustering model includes a project type clustering model and a customer demand clustering model.

[0105] The project completion time prediction model is based on historical project data, such as project size, complexity, resource allocation, etc., and uses regression analysis methods to establish a mathematical relationship between project completion time and these factors, so as to predict the completion time of new projects. Collect historical project data and perform preprocessing such as cleaning, deduplication, and missing value processing. Select features that affect project completion time from the preprocessed data, such as project size, complexity, resource allocation, etc. Use algorithms such as linear regression or decision tree regression to establish a mathematical relationship model between project completion time and features. Use historical project data to train the model and evaluate the model's prediction performance through methods such as cross-validation. Apply the trained model to a new project, input the feature data of the new project, and output the predicted project completion time.

[0106] The cost prediction model uses historical project data and combines cost estimation technology to establish a prediction model between project cost and project characteristics, which is used to estimate the cost of new projects. Select features that affect project costs, such as project scale, material prices, labor costs, etc., and use algorithms such as multiple linear regression or random forest regression to establish a mathematical relationship model between project costs and features.

[0107] The market demand forecasting model is based on historical market data, such as sales, market share, and competitor conditions, and uses time series analysis or machine learning algorithms to predict future market demand and trends. Select features that affect market demand, such as sales, market share, and competitor conditions, and use machine learning algorithms such as ARIMA time series analysis or support vector machine (SVM) to establish a forecasting model between market demand and features.

[0108] Classification models are used to divide data items into different categories or groups. Classification models include project risk level classification models, supplier credit evaluation classification models, and engineering quality classification models.

[0109] The project risk level classification model is based on project characteristic data, such as project scale, complexity, historical risk events, etc., and uses machine learning algorithms such as decision trees, support vector machines or neural networks to classify project risk levels.

[0110] The supplier credit evaluation classification model uses the supplier's historical performance data, such as on-time delivery rate, quality pass rate, contract fulfillment, etc., to establish a credit evaluation index system, and adopts a classification algorithm to classify the supplier's credit rating.

[0111] The project quality classification model is based on project quality inspection data, such as material quality, construction technology, acceptance results, etc., and uses machine learning algorithms to classify project quality to determine whether the project meets the predetermined standards.

[0112] Clustering models are used to divide data items into similar groups or clusters. Clustering models include project type clustering models and customer demand clustering models.

[0113] The project type clustering model is based on project feature data, such as project scale, industry field, technical difficulty, etc., and uses clustering algorithms (such as K-means, hierarchical clustering, etc.) to classify projects into types in order to better manage and allocate resources.

[0114] The customer demand clustering model uses historical customer demand data, such as purchase records, service requests, feedback, etc., and adopts the clustering algorithm K-means to divide customer needs in order to better understand customer needs and formulate targeted marketing strategies.

[0115] By adopting technical means such as regression analysis, machine learning algorithms and clustering algorithms, we have achieved effective analysis and prediction of project completion time, cost, market demand, project risk level, supplier credit evaluation, engineering quality, project type and customer needs.

[0116] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0117] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A digital project management platform for construction companies. Features: Includes user interface layer, business logic layer, infrastructure layer and data access layer; The user interface layer includes a user interaction module and a rights management module; The user interaction module is used to provide a visual user interface and process the interaction logic between the user and the platform; the permission management module is used to manage and control user access rights; The business logic layer includes a basic management module and a fusion analysis module; The basic management module includes a project management unit, a material procurement management unit, a construction management unit, a quality control unit, a bidding management unit, a safety risk management unit, a subcontract management unit and a business management unit; wherein: The project management unit is used to handle the overall business processes related to the project, including project planning, progress tracking, cost control and resource allocation; The material procurement management unit is used to process business processes related to material procurement, including procurement plan formulation, supplier selection, purchase order generation and procurement execution; The construction management unit is used to process business processes related to the construction site, including construction progress control, construction quality management and construction safety management; The quality control unit is used to process business processes related to engineering quality, including quality plan formulation, quality control standard setting and quality inspection execution; The bidding management unit is used to assist enterprises in managing the entire bidding process of engineering projects, including bidding information management, bidding preparation and compilation, bidding review and decision-making; The safety risk management unit is used to assess and manage safety risks in the project, including recording of safety hazards, assessment of risk levels and formulation of risk response measures; The subcontract management unit is responsible for handling business processes related to subcontracting, including the selection of subcontractors, the signing of subcontract contracts and the execution of subcontract work; The business management unit is responsible for handling business-related business processes, including contract signing, modification, execution and settlement; The fusion analysis module includes a data integration unit and an analysis model construction unit; the data integration unit is used to standardize the data of each business logic layer module, including data format and naming specifications, and through data integration technology, centrally store and manage the relevant data scattered in each business logic layer module to form a unified data view; the analysis model construction unit is used to build data analysis models according to business needs, including prediction models, classification models and clustering models, and use machine learning algorithms to conduct in-depth mining and analysis of the integrated data; The infrastructure layer includes a database module, a service management module and a gateway module; the database module provides data storage functions, including a data cache unit, a persistent storage unit and a column storage unit, the data cache unit is used to temporarily store frequently accessed data, the persistent storage unit is used to store important data for a long time, and the column storage unit is used to store and analyze a large amount of structured data; the service management module uses a microservice architecture to uniformly manage the modules of the business logic layer; the gateway module provides connection services to the user interface layer, establishes a channel for data transmission, and matches the target microservice instance accessed by the user interface layer through the routing address; The data access layer includes a data interface module and a database connection module; the data interface module is used to provide the HTTP interface and Websocket message push for page requests to the user interface layer; the database connection module establishes a connection channel between the business logic layer and the database module, allowing both to perform safe and stable data reading and writing operations.

2. A digital project management platform for construction enterprises according to claim 1, It is characterized in that The service management module: Provide unified registration, status monitoring and message bus communication functions for microservice instances; Automatically manage and schedule microservice instances, including service deployment, start, stop, and restart; Perform data monitoring and log management on microservices, and collect service operation data and log information.

3. A digital project management platform for construction enterprises according to claim 2, Features: The message bus adopts the communication mechanism of the event bus, so that the microservices in the service layer can communicate loosely through events.

4. A digital project management platform for construction enterprises according to claim 3, Its characteristics are: The database module adopts a dual-active architecture, including an active node and a standby node. The two nodes back up each other when processing data. When the active node fails, needs maintenance or upgrade, the standby node takes over the service.

5. A digital project management platform for construction enterprises according to claim 4, Features: The prediction model includes a project completion time prediction model, a cost prediction model and a market demand prediction model; the classification model includes a project risk level classification model, a supplier credit evaluation classification model and an engineering quality classification model; the clustering model includes a project type clustering model and a customer demand clustering model.

6. A digital project management platform for construction enterprises according to claim 5, It is characterized in that The data interface module: Provides HTTP interface for page requests, used to receive page requests sent by the user interface layer; Provides a Websocket message push interface to implement real-time message push from the server to the user interface layer; Parse and process received page requests and message push requests, and call corresponding microservices to perform business logic processing based on the type and content of the request; Return the processed results of the microservice to the user interface layer.

7. A digital project management platform for construction enterprises according to claim 6, Features: The gateway module maintains a routing table to record the address information of each microservice instance; according to the routing address in the request of the user interface layer, it matches in the routing table, finds the corresponding target microservice instance, and forwards the request to the instance.

8. A digital project management platform for construction enterprises according to claim 7, Features: The data integration unit defines and identifies each business logic layer module as a data source, and formulates a data extraction strategy based on business requirements and data characteristics. The extraction strategy includes a full extraction measurement and an incremental extraction strategy.

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